Microbiome–metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient
(2024) In Nature Microbiology 9(11). p.2892-2908- Abstract
Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This... (More)
Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO2 and CH4 porewater variations. Our study showcases insights gained by using feature-level data and microorganism–metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.
(Less)
- author
- author collaboration
- organization
- publishing date
- 2024-11-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- greenhouse gas emissions, permafrost, ecology, trait based model, microbiology
- in
- Nature Microbiology
- volume
- 9
- issue
- 11
- pages
- 17 pages
- publisher
- Springer Nature
- external identifiers
-
- scopus:85205349343
- pmid:39354152
- ISSN
- 2058-5276
- DOI
- 10.1038/s41564-024-01800-z
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s) 2024.
- id
- 80364ffe-3200-4d11-be2f-ddfde19da87c
- date added to LUP
- 2024-12-11 11:04:11
- date last changed
- 2025-07-10 04:09:37
@article{80364ffe-3200-4d11-be2f-ddfde19da87c, abstract = {{<p>Interactions between microbiomes and metabolites play crucial roles in the environment, yet how these interactions drive greenhouse gas emissions during ecosystem changes remains unclear. Here we analysed microbial and metabolite composition across a permafrost thaw gradient in Stordalen Mire, Sweden, using paired genome-resolved metagenomics and high-resolution Fourier transform ion cyclotron resonance mass spectrometry guided by principles from community assembly theory to test whether microorganisms and metabolites show concordant responses to changing drivers. Our analysis revealed divergence between the inferred microbial versus metabolite assembly processes, suggesting distinct responses to the same selective pressures. This contradicts common assumptions in trait-based microbial models and highlights the limitations of measuring microbial community-level data alone. Furthermore, feature-scale analysis revealed connections between microbial taxa, metabolites and observed CO<sub>2</sub> and CH<sub>4</sub> porewater variations. Our study showcases insights gained by using feature-level data and microorganism–metabolite interactions to better understand metabolic processes that drive greenhouse gas emissions during ecosystem changes.</p>}}, author = {{Freire-Zapata, Viviana and Holland-Moritz, Hannah and Cronin, Dylan R. and Aroney, Sam and Smith, Derek A. and Wilson, Rachel M. and Ernakovich, Jessica G. and Woodcroft, Ben J. and Bagby, Sarah C. and Mondav, Rhiannon and Hodgkins, Suzanne B. and Zayed, Ahmed A. and Varner, Ruth K. and Saleska, Scott R. and Ibba, Michael and Ferriere, Regis and Fahnestock, Maria Florencia and E. Cross, Jennifer and Rich, Virginia I. and Sullivan, Matthew B. and Stegen, James C. and Tfaily, Malak M.}}, issn = {{2058-5276}}, keywords = {{greenhouse gas emissions; permafrost; ecology; trait based model; microbiology}}, language = {{eng}}, month = {{11}}, number = {{11}}, pages = {{2892--2908}}, publisher = {{Springer Nature}}, series = {{Nature Microbiology}}, title = {{Microbiome–metabolite linkages drive greenhouse gas dynamics over a permafrost thaw gradient}}, url = {{http://dx.doi.org/10.1038/s41564-024-01800-z}}, doi = {{10.1038/s41564-024-01800-z}}, volume = {{9}}, year = {{2024}}, }